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Tainan City, Taiwan
Avatar of 潘揚燊.
Avatar of 潘揚燊.
智慧製造全端開發工程師 @聯華電子股份有限公司
2022 ~ Present
AI工程師、機器學習工程師、深度學習工程師、影像演算法工程師、資料科學家、Ai Application Engineer,Machine Learning Engineer,Deep Learning Engineer,Data Scientist
Within one month
潘揚燊 ㄕㄣ Shen Pan Kaohsiung City,Taiwan •  [email protected] 希望職務:人工智慧、機器視覺應用開發工程師 現任 : 聯華電子 RPA 平台全端開發工程師 您好,我是潘揚燊,目前任職於 聯華電子 , 擔任 智慧製造 全端開發工程師 , 畢業於元智大學工業工程與管理學系研
Python
Qt
Git
Employed
Ready to interview
Full-time / Interested in working remotely
4-6 years
元智大學 Yuan Ze University
工業工程與管理學系所
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Senior Data Scientist @PTI 力成科技
2016 ~ Present
大數據分析,資料科學家,資料工程師,AI工程師
Within one month
Data Augmentation for Rare Defect Images
Signal Processing & Recognition
Administrator for Engineering Data Analysis System
Employed
Open to opportunities
Full-time / Interested in working remotely
6-10 years
逢甲大學
Applied Mathematics
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Avatar of the user.
Technical Project Manager/技術專案管理 @CM Visual Technology Corporation/微采視像科技股份有限公司
2016 ~ Present
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
More than one year
6 Sigma
光學系統架設
產品開發企劃
Employed
Full-time / Interested in working remotely
6-10 years
National Sun Yat-Sen University/國立中山大學
Optoelectronic Engineering/光電工程
Avatar of Eason Huang.
Offline
Avatar of Eason Huang.
Offline
缺陷分析工程師 @TSMC
2014 ~ 2017
資料科學家/機器學習工程師
More than one year
and machine learning engineer. For job skills/tools, learned to program by VBA, SQL and some python because of the large amount of data analysis at work, and also try to apply machine learning to work. Currently working and studying hard to become a data scientist. 資料科學家/機器學習工程師 Taipei Special Municipality,TW [email protected] 工作經歷 TSMC, 資深缺陷分析系統工程師, Jul 2017 ~ 現在 2017年7月開始轉任
word
powerpoint
Python
Full-time / Interested in working remotely
4-6 years
清華大學
物理系
Avatar of Ling-Yu-Chien.
Avatar of Ling-Yu-Chien.
個人自媒體經營 @Freelance
2021 ~ Present
資深企劃或專案管理
Within one month
運動力學、人工智慧、3D引擎、3D音場技術,創造出極度擬真的海洋虛擬實境。 從業務進案後開始參與,根據客戶需求進行背景資料研讀、撰寫提案、統籌企劃、專家顧問聯繫溝通,確認科學資料正確性。 影片腳本撰寫互動遊戲腳本撰寫、各式展示文案或
專案管理
Google Drive
Premiere Pro
Employed
Open to opportunities
Full-time / Remote Only
10-15 years
台灣藝術大學
電影系
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Sr. UX Researcher @17LIVE
2021 ~ Present
UX Designer, User Researcher
Within six months
User Research
User Experience Design
Usability Testing
Employed
Not open to opportunities
Full-time / Interested in working remotely
6-10 years
國立清華大學
社會學, 哲學
Avatar of 梁力基.
Within two months
曲線陡峭,因此大部份的專案,我採用 Riverpod。 2. 過早的最佳化,通常會是場災難,因為表示無法更彈性的面對客戶變更需求。 如資料庫的資料結構,實際上就是平衡負載與 cache 的藝術,但過早的最佳化,容易變成災難現場 3. 高度重覆性的工作,應該創
Linux
PHP
Flutter(APP)
Unemployed
Open to opportunities
10-15 years

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Technical Skills
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More than one year
Senior Engineer/TSMC
TSMC
2017 ~ Present
台灣台南市
Professional Background
Current status
Job Search Progress
Professions
Data Engineer
Fields of Employment
Semiconductor
Work experience
4-6 years
Management
Skills
word
powerpoint
Python
keras
NumPy
Pandas
pytorch
Arduino
Raspberry Pi
VBA-Excel
SQL
SQLite
Jupyter Notebook
Languages
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資料科學家/機器學習工程師
Job types
Full-time
Locations
Remote
Interested in working remotely
Freelance
Educations
School
清華大學
Major
物理系
Print

Eason Huang

Github: https://github.com/ychuangab
Kaggle: https://www.kaggle.com/uvxy1234
Leetcode: https://leetcode.com/uvxy1234/

Currently work in Tainan Science Park TSMC as a senior process integration engineer(PIE). Main business is to solve the defect problem of the wafer.
Majored in physics both for master and bachelor degree.

Experienced in analyzing wafer low yield and defect problems, familiar with the way that defect is discovered and the mechanism of defect formation. Also experienced on develop defect analysis system with IT and machine learning engineer.

For job skills/tools, learned to program by VBA, SQL and some python because of the large amount of data analysis at work, and also try to apply machine learning to work.

Currently working and studying hard to become a data scientist.

資料科學家/機器學習工程師
Taipei Special Municipality,TW
[email protected]


Profile 04 00@2x

工作經歷

TSMC, 資深缺陷分析系統工程師, Jul 2017 ~ 現在

2017年7月開始轉任缺陷分析(Defect Analysis)的系統部門,同時升任資深工程師。

主要職責:
(1) 建立跨廠區跨部門最佳化分配缺陷掃描機台的資源之系統(智慧化抽樣系統, Intelligence Sampling Scaning)

(2) 缺陷圖像自動分類系統(Auto Defect Classification, ADC),即與IT合作建立深度學習網路搭配工程師labeling做的監督式學習來達到自動分類,架構採用Inception Resnet V2的pre-trained model做transfer learning

TSMC, 缺陷分析工程師, Aug 2014 ~ Jul 2017

防守並解決能夠直接被光學式/電子式掃描機台所檢查的缺陷,舉凡像是晶面/晶背刮傷(Scratch),機台掉到晶面的落塵(Particle)或是微小的破洞以及光阻的殘留所造成的patterning failure,並協助製程/設備工程師發展defect reduction相關CIP

TSMC, 製程整合工程師, Sep 2013 ~ Aug 2014

透過各製程站別的關鍵結構(Critical Dimension, CD)的量測,以及晶圓出貨前的允收測試(Wafer Acceptance Test, WAT)之觀測統計對應製程的變化,結合製程流程的順序性,以發掘出風險因子(可能是機台、機台程式、光罩、原物料…等)。

學歷

清華大學, 碩士學位, 物理系, 2011 ~ 2013

論文題目: W頻帶100GHz TE01模式之磁旋返波震盪器(Gyro-BWO)效率研究


摘要:
磁旋返波振盪器係利用電子迴旋脈射機制產生同調電磁波,利用電子與波的內部反饋迴路產生振盪,而非採用傳統共振腔結構,因而有連續可調的寬頻調頻之特性,在研究與實用上都有很大的發展潛力。然而,因為其場型會往作用結構的前端集中,不利於電子與波的交互作用,所以其效率通常相當低,因此探討磁旋返波振盪器的基本特性與效率之提升是本篇論文的主要脈絡。

做為與以往Ka頻段的磁旋返波振盪器模擬結果之比較及驗證,本文根據已設計好的W頻段MIG電子槍之工作參數為依據,以W頻段的磁旋返波振盪器為研究對象,做理論上的計算探討。
在小訊號的線性操作之下,根據電子與電磁波的交互作用形式,能量吸放的次數之不同,造成不同的軸向模式;而在飽和電流的非線性操作下,因為內部反饋迴路的縮短,造成場型逐漸往上游端收縮,因而形成效率對電流或長度的飽和現象。

接著,我們根據以往經驗提出的方法,適當地傾斜磁旋返波振盪器之作用結構的半徑,以提升效率。模擬結果顯示,我們的雙傾斜結構設計在振盪頻率94GHz至99GHz可給出約23%至30%的效率,達到穩定而寬頻的高功率輸出。

中央大學, 理學士(BS), 物理系, 2007 ~ 2011

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nam porttitor dapibus ipsum ut efficitur. Aliquam feugiat nec sem dapibus blandit.

Resume
Profile

Eason Huang

Github: https://github.com/ychuangab
Kaggle: https://www.kaggle.com/uvxy1234
Leetcode: https://leetcode.com/uvxy1234/

Currently work in Tainan Science Park TSMC as a senior process integration engineer(PIE). Main business is to solve the defect problem of the wafer.
Majored in physics both for master and bachelor degree.

Experienced in analyzing wafer low yield and defect problems, familiar with the way that defect is discovered and the mechanism of defect formation. Also experienced on develop defect analysis system with IT and machine learning engineer.

For job skills/tools, learned to program by VBA, SQL and some python because of the large amount of data analysis at work, and also try to apply machine learning to work.

Currently working and studying hard to become a data scientist.

資料科學家/機器學習工程師
Taipei Special Municipality,TW
[email protected]


Profile 04 00@2x

工作經歷

TSMC, 資深缺陷分析系統工程師, Jul 2017 ~ 現在

2017年7月開始轉任缺陷分析(Defect Analysis)的系統部門,同時升任資深工程師。

主要職責:
(1) 建立跨廠區跨部門最佳化分配缺陷掃描機台的資源之系統(智慧化抽樣系統, Intelligence Sampling Scaning)

(2) 缺陷圖像自動分類系統(Auto Defect Classification, ADC),即與IT合作建立深度學習網路搭配工程師labeling做的監督式學習來達到自動分類,架構採用Inception Resnet V2的pre-trained model做transfer learning

TSMC, 缺陷分析工程師, Aug 2014 ~ Jul 2017

防守並解決能夠直接被光學式/電子式掃描機台所檢查的缺陷,舉凡像是晶面/晶背刮傷(Scratch),機台掉到晶面的落塵(Particle)或是微小的破洞以及光阻的殘留所造成的patterning failure,並協助製程/設備工程師發展defect reduction相關CIP

TSMC, 製程整合工程師, Sep 2013 ~ Aug 2014

透過各製程站別的關鍵結構(Critical Dimension, CD)的量測,以及晶圓出貨前的允收測試(Wafer Acceptance Test, WAT)之觀測統計對應製程的變化,結合製程流程的順序性,以發掘出風險因子(可能是機台、機台程式、光罩、原物料…等)。

學歷

清華大學, 碩士學位, 物理系, 2011 ~ 2013

論文題目: W頻帶100GHz TE01模式之磁旋返波震盪器(Gyro-BWO)效率研究


摘要:
磁旋返波振盪器係利用電子迴旋脈射機制產生同調電磁波,利用電子與波的內部反饋迴路產生振盪,而非採用傳統共振腔結構,因而有連續可調的寬頻調頻之特性,在研究與實用上都有很大的發展潛力。然而,因為其場型會往作用結構的前端集中,不利於電子與波的交互作用,所以其效率通常相當低,因此探討磁旋返波振盪器的基本特性與效率之提升是本篇論文的主要脈絡。

做為與以往Ka頻段的磁旋返波振盪器模擬結果之比較及驗證,本文根據已設計好的W頻段MIG電子槍之工作參數為依據,以W頻段的磁旋返波振盪器為研究對象,做理論上的計算探討。
在小訊號的線性操作之下,根據電子與電磁波的交互作用形式,能量吸放的次數之不同,造成不同的軸向模式;而在飽和電流的非線性操作下,因為內部反饋迴路的縮短,造成場型逐漸往上游端收縮,因而形成效率對電流或長度的飽和現象。

接著,我們根據以往經驗提出的方法,適當地傾斜磁旋返波振盪器之作用結構的半徑,以提升效率。模擬結果顯示,我們的雙傾斜結構設計在振盪頻率94GHz至99GHz可給出約23%至30%的效率,達到穩定而寬頻的高功率輸出。

中央大學, 理學士(BS), 物理系, 2007 ~ 2011

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nam porttitor dapibus ipsum ut efficitur. Aliquam feugiat nec sem dapibus blandit.